A Multi-Modal State and Measurement Filter for RSO Tracking

Joint Space Operations Center under the United States Strategic Command employs a worldwide network of 29 sensors, known as the Space Surveillance Network (SSN), to track more than 17,000 man-made objects in Earth orbit with sizes 10 centimeters or larger. Decisive Analytics Corporation and the University of Texas Austin Center for Space Research propose an innovate framework for solving stochastic differential equations that will allow non-Gaussian uncertainty estimates to be predicted into the future. This will result in more accurate predictions that can be used for conjunction analysis and other function leading to better space situational awareness. The Phase 1 program can be naturally extended in Phase 2 to address the fusion of non-Gaussian measurement errors. BENEFIT: The proposed technology will increase the accuracy in the prediction of the future ephemeris of space objects. This will increase the Joint Space Operations Center ability to support its mission to analyze new space launches and evaluate orbital insertion; detect new man-made objects in space; inform NASA and other government entities if objects might interfere with the orbits of national assets; and to prevent a returning space object, which looks like a missile to radar, from triggering missile-attack sensors.